Research on digital media art creation based on vision and generation algorithm

This paper aims to explore the application and core position of vision and generation algorithm in digital media art. Through deep learning and computer vision technology, these algorithms not only process image and video data efficiently, but also give new expressive force and freedom to artistic creation. This paper summarizes the basic principles and applications of visual algorithms, including content recognition, video analysis, digital media art creation and scene reconstruction. The specific practices of image classification, target detection, pose estimation and so on are introduced in detail, and the construction of convolutional neural network (CNN) and its application in image classification are discussed in depth. The paper also introduces the common network architectures such as VGg, perception and RESNET, and shows the interest and practicability of the algorithm through the cases of target detection and neural style migration.